# #!/usr/bin/python
# # -*- coding: UTF-8 -*-
#
# # face_detect.py
#
# # Face Detection using OpenCV. Based on sample code from:
# # http://www.pythontab.com
# # http://www.pythontab.com/html/2012/pythonhexinbiancheng_1227/68.html
#
# # Usage: python face_detect.py
#
# import sys, os
# # 引入opencv库中的相应组件
# import cv2
# from opencv.cv import *
# from opencv.highgui import *
# # 引入PIL库
# from PIL import Image, ImageDraw
# from math import sqrt
#
#
# def detectObjects(image):
#     # 首先把图片转换为灰度模式，以便找到人脸位置
#     grayscale = cvCreateImage(cvSize(image.width, image.height), 8, 1)
#     cvCvtColor(image, grayscale, CV_BGR2GRAY)
#
#     storage = cvCreateMemStorage(0)
#     cvClearMemStorage(storage)
#     cvEqualizeHist(grayscale, grayscale)
#
#     cascade = cvLoadHaarClassifierCascade('/usr/share/opencv/haarcascades/haarcascade_frontalface_default.xml',cvSize(1, 1))
#     faces = cvHaarDetectObjects(grayscale, cascade, storage, 1.1, 2, CV_HAAR_DO_CANNY_PRUNING, cvSize(20, 20))
#
#     result = []
#     for f in faces:
#         result.append((f.x, f.y, f.x + f.width, f.y + f.height))
#
#     return result
#
#
# def grayscale(r, g, b):
#     return int(r * .3 + g * .59 + b * .11)
#
#
# def process(infile, outfile):
#     image = cvLoadImage(infile)
#     if image:
#         faces = detectObjects(image)
#
#     im = Image.open(infile)
#
#     if faces:
#         draw = ImageDraw.Draw(im)
#         for f in faces:
#             draw.rectangle(f, outline=(255, 0, 255))
#
#         im.save(outfile, "JPEG", quality=100)
#     else:
#         print("Error: cannot detect faces on %s" % infile)
#
#
# if __name__ == "__main__":
#     process('input.jpg', 'output.jpg')